Final Exam: AI Apprentice

WHAT YOU WILL LEARN

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  Distinguish between an intelligent system and pre-programmed logic using several definitions of artificial intelligence and specify the scope of ai applications
  

  compare the major differences between intelligent systems including search algorithms, machine learning systems, probabilistic models, neural networks, and reinforcement learning systems
  

  list the tools commonly used for hci studies and specify their purpose
  

  recognize the multidisciplinary nature of hci and list the areas most involved in the studies
  

  describe basic concepts in computer vision
  

  compare cognitive modeling and artificial intelligence
  

  specify multiple disciplines involved in cognitive modeling and describe their role
  

  illustrate how computer science is connected with cognitive modeling
  

  define hybrid learning and describe examples of its use
  

  specify how ai has affected cognitive modeling and enhanced its power
  

  describe and distinguish between different types of modeling tools
  

  define reactive and limited memory systems and describe reactive ai, limited memory ai, and a combination of both
  

  list the steps needed to create an object detection neural network and describe how object detection is performed
  

  compare image processing to traditional methods of solving image problems
  

  describe how a cv is used in the automotive industry and its role in the development of self-driving cars
  

  describe how the success of ai solutions in narrow fields is a combination of adequate task, good data, and appropriate tools and list fields that are most impacted by ai
  

  configure the python environment for developing ai
  

  describe how a cv is used in the aerospace industry and list the responsibilities of a cv system on an aircraft
  

  describe the role of a user-oriented approach in the success of ai applications
  

  define human-computer interaction as a multidisciplinary field essential to computer science and describe its importance for the success of software companies
  

  describe the steps needed to create deep learning models and identify guidelines for using them
  

  classify different types of convolutional neural networks by their structure and purpose
  

  recognize the most recent research breakthroughs in ai and how they might be used, and list applications of ai that are already on the market
  

  describe true research on self-aware ai and compare it with common views on the future of ai
  

  describe the role computer vision plays in the industry and associated trends
  

  identify the main steps in the hci process and name multiple methodologies used
  

  describe the steps needed to create machine learning models and identify guidelines for using them
  

  define general intelligence in terms of ai tools known today and recognize the amount of work needed to achieve any agi
  

  define narrow artificial intelligence, describe multiple areas of its use in the modern world, and recognize the latest research
  

  identify different types of cognitive models and name popular cognitive modeling applications
• 

  troubleshoot usability of an ai application prototype
  

  specify why explainability research in ai is required for developing user-friendly applications
  

  name and describe different types of cognitive learning
  

  compare image processing to computer vision
  

  list the components involved in human-computer interaction (hci) studies and specify their role
  

  describe factors that make python one of the most popular programming languages
  

  describe the principles of prototyping and distinguish between a prototype and a demonstration product
  

  specify the role of anaconda in keeping clear working environments
  

  recognize how the performance of convolutional neural network revolutionized cv
  

  illustrate how ai can be part of a computer vision solution
  

  describe how a cv is used in electronics and why cheap consumer electronics are not possible without cv
  

  describe why using artificial intelligence is becoming important today and list multiple factors that make the use of ai in business necessary for competitive advantage
  

  describe and distinguish between multiple python ai libraries
  

  specify the advantages of jupyter notebooks and create jupyter notebook files connected to the appropriate kernel environment
  

  describe the python programming language and recognize its role in ai development
  

  identify reasons why the iterative approach has shown to be most practical when designing software applications
  

  describe distinguishing features of adaptive, interactive, iterative, and contextual cognitive models
  

  compare artificial superintelligence with artificial general intelligence and specify the multiple factors needed to achieve them
  

  identify the advantages of using python when developing ai
  

  differentiate between interpreted and compiled programming languages
  

  describe the principles of the anthropomorphic approach to hci
  

  compare multiple approaches to ai development to distinguish key differences between them
  

  describe why big data improve ai performance and accuracy by specifying how collecting large amounts of data creates opportunities for new ai development and research
  

  recognize how ci/cd became essential to any kind of software company and list multiple factors that make ci/cd important for ai companies
  

  define symbolic learning and describe examples of its use
  

  name and describe basic concepts in and cognition and cognitive modeling
  

  specify the advantages of the google collab environment and create files in the environment
  

  recognize major ai tools used in the industry
  

  compare the performance and functionality of python ai toolbox to r ai toolbox
  

  identify and describe problems that can be solved using computer vision